National and Subnational estimates for Russia

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally in Russia. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Table of Contents


Using data available up to the: 2020-07-30

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by region


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-07-18) in Russia, stratified by region, can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Regions with fewer than 40 confirmed cases reported on a single day are not included in the analysis (light grey).

National summary

Summary (estimates as of the 2020-07-18)

Table 1: Latest estimates (as of the 2020-07-18) of the number of confirmed cases by date of infection, the expected change in daily confirmed cases, the effective reproduction number, the doubling time (when negative this corresponds to the halving time), and the adjusted R-squared of the exponential fit. The mean and 90% credible interval is shown for each numeric estimate.
Estimate
New confirmed cases by infection date 6604 (6247 – 6936)
Expected change in daily cases Likely increasing
Effective reproduction no. 1 (1 – 1)
Doubling/halving time (days) 130 (66 – 7500)
Adjusted R-squared 0.56 (0.14 – 0.93)

Confirmed cases, their estimated date of infection, and time-varying reproduction number estimates


Figure 2: A.) Confirmed cases by date of report (bars) and their estimated date of infection. B.) Time-varying estimate of the effective reproduction number. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Estimates from existing data are shown up to the 2020-07-18 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Time-varying rate of growth and doubling time


Figure 3: A.) Time-varying estimate of the rate of growth, B.) Time-varying estimate of the doubling time in days (when negative this corresponds to the halving time), C.) The adjusted R-squared estimates indicating the goodness of fit of the exponential regression model (with values closer to 1 indicating a better fit). Estimates from existing data are shown up to the 2020-07-18. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Regional Breakdown

Data availability

Limitations

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 4: Confirmed cases with date of infection on the 2020-07-18 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 5: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-07-18 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 6: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-07-18 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 7: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-07-18 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 8: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-07-18 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-07-18)

Table 2: Latest estimates (as of the 2020-07-18) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Adygea Republic 35 (23 – 46) Likely increasing 1.2 (0.9 – 1.5) 13 (5.6 – -39)
Altai Krai 147 (124 – 169) Decreasing 0.9 (0.8 – 1) -19 (-99 – -10)
Altai Republic 29 (15 – 38) Unsure 1 (0.7 – 1.3) 190 (8.4 – -9.4)
Amur Oblast 33 (22 – 43) Unsure 1 (0.7 – 1.2) -42 (13 – -8.2)
Arkhangelsk Oblast 74 (57 – 89) Likely decreasing 0.9 (0.7 – 1) -18 (160 – -8.5)
Astrakhan Oblast 35 (24 – 46) Unsure 1 (0.8 – 1.2) -71 (13 – -9.5)
Bashkortostan Republic 39 (27 – 50) Likely decreasing 0.9 (0.7 – 1.1) -23 (24 – -7.7)
Belgorod Oblast 45 (33 – 57) Unsure 1 (0.8 – 1.2) 180 (11 – -13)
Bryansk Oblast 28 (17 – 38) Unsure 0.9 (0.7 – 1.2) -52 (11 – -7.9)
Buryatia Republic 38 (25 – 49) Unsure 1 (0.8 – 1.2) -100 (12 – -9.8)
Chechen Republic 14 (5 – 20) Unsure 1 (0.7 – 1.4) 90 (5.9 – -6.9)
Chelyabinsk Oblast 135 (112 – 157) Unsure 1 (0.9 – 1.2) 75 (16 – -29)
Chuvashia Republic 45 (33 – 58) Unsure 0.9 (0.7 – 1.1) -46 (17 – -9.8)
Dagestan Republic 43 (29 – 55) Unsure 1 (0.8 – 1.2) 2200 (12 – -11)
Ingushetia Republic 25 (14 – 34) Unsure 1 (0.7 – 1.2) -77 (10 – -7.9)
Irkutsk Oblast 178 (152 – 202) Unsure 1 (0.9 – 1.1) 11000 (25 – -24)
Ivanovo Oblast 45 (30 – 57) Likely decreasing 0.9 (0.7 – 1.1) -22 (30 – -7.9)
Kabardino-Balkarian Republic 46 (34 – 58) Unsure 1 (0.8 – 1.2) -100 (13 – -11)
Kaliningrad Oblast 17 (8 – 23) Unsure 0.9 (0.6 – 1.3) -56 (7.9 – -6.3)
Kalmykia Republic 37 (24 – 48) Likely decreasing 0.8 (0.6 – 1.1) -12 (1900 – -5.7)
Kaluga Oblast 28 (17 – 38) Likely decreasing 0.9 (0.6 – 1.1) -24 (15 – -6.8)
Kamchatka Krai 37 (24 – 47) Unsure 1 (0.8 – 1.2) 440 (11 – -11)
Karachay-Cherkess Republic 36 (23 – 48) Likely decreasing 0.8 (0.6 – 1) -12 (200 – -5.7)
Karelia Republic 35 (23 – 48) Unsure 1.1 (0.8 – 1.3) 43 (8.2 – -13)
Kemerovo Oblast 69 (51 – 83) Likely increasing 1.1 (0.9 – 1.3) 23 (8.8 – -39)
Khabarovsk Krai 124 (102 – 145) Unsure 1 (0.9 – 1.2) 100 (17 – -25)
Khakassia Republic 43 (30 – 55) Unsure 1.1 (0.9 – 1.3) 29 (8.2 – -19)
Khanty-Mansi Autonomous Okrug 211 (182 – 239) Unsure 1 (0.9 – 1.1) -65 (44 – -19)
Kirov Oblast 55 (39 – 68) Unsure 1 (0.8 – 1.2) 180 (12 – -14)
Komi Republic 57 (41 – 71) Unsure 1 (0.8 – 1.1) -60 (17 – -11)
Kostroma Oblast 23 (13 – 31) Unsure 0.9 (0.7 – 1.2) -38 (11 – -7.1)
Krasnodar Krai 92 (73 – 107) Likely increasing 1.1 (1 – 1.2) 28 (10 – -44)
Krasnoyarsk Krai 162 (136 – 189) Likely increasing 1.1 (1 – 1.2) 23 (11 – -300)
Kurgan Oblast 42 (29 – 54) Unsure 0.9 (0.7 – 1.1) -35 (18 – -8.8)
Kursk Oblast 34 (21 – 45) Unsure 1 (0.8 – 1.3) 120 (9.5 – -11)
Leningrad Oblast 46 (31 – 57) Unsure 1 (0.8 – 1.2) 480 (12 – -13)
Lipetsk Oblast 36 (24 – 48) Unsure 1 (0.8 – 1.2) -480 (11 – -10)
Magadan Oblast 36 (22 – 45) Likely increasing 1.3 (1 – 1.6) 11 (5 – -86)
Mari El Republic 31 (18 – 40) Unsure 1 (0.8 – 1.3) 87 (8.5 – -11)
Mordovia Republic 36 (24 – 47) Unsure 1 (0.8 – 1.2) -4700 (11 – -11)
Moscow 686 (623 – 762) Increasing 1.1 (1 – 1.1) 32 (19 – 120)
Moscow Oblast 150 (123 – 172) Unsure 1 (0.9 – 1.1) -92 (28 – -18)
Murmansk Oblast 167 (143 – 190) Unsure 1 (0.9 – 1.1) -190 (28 – -21)
Nizhny Novgorod Oblast 200 (172 – 229) Unsure 1 (0.9 – 1.1) -1100 (26 – -25)
North Ossetia - Alania Republic 24 (14 – 33) Unsure 1 (0.7 – 1.2) -66 (9.9 – -7.8)
Novgorod Oblast 41 (29 – 53) Unsure 1 (0.8 – 1.2) -120 (13 – -10)
Novosibirsk Oblast 107 (88 – 125) Unsure 1 (0.9 – 1.1) -120 (23 – -16)
Omsk Oblast 115 (97 – 134) Unsure 1 (0.9 – 1.1) 160 (18 – -23)
Orel Oblast 28 (18 – 38) Unsure 0.9 (0.7 – 1.1) -21 (17 – -6.6)
Orenburg Oblast 113 (95 – 132) Unsure 1 (0.9 – 1.1) -510 (20 – -19)
Penza Oblast 45 (32 – 56) Unsure 1.1 (0.8 – 1.3) 44 (9.2 – -16)
Perm Krai 76 (58 – 90) Unsure 1 (0.8 – 1.1) -61 (22 – -12)
Primorsky Krai 110 (89 – 129) Likely increasing 1.1 (1 – 1.3) 24 (10 – -67)
Pskov Oblast 31 (19 – 41) Unsure 1.1 (0.8 – 1.4) 28 (6.9 – -13)
Rostov Oblast 133 (108 – 154) Likely increasing 1.1 (1 – 1.3) 23 (11 – -200)
Ryazan Oblast 34 (22 – 45) Unsure 1 (0.8 – 1.2) -81 (12 – -9.4)
Saint Petersburg 190 (157 – 214) Likely decreasing 0.9 (0.8 – 1) -40 (61 – -15)
Sakha (Yakutiya) Republic 49 (34 – 61) Unsure 1 (0.8 – 1.2) -94 (15 – -11)
Sakhalin Oblast 63 (47 – 76) Unsure 1 (0.9 – 1.2) 170 (13 – -15)
Samara Oblast 45 (31 – 56) Likely decreasing 0.9 (0.7 – 1.1) -23 (27 – -7.9)
Saratov Oblast 96 (78 – 112) Unsure 1 (0.9 – 1.1) 450 (17 – -19)
Sevastopol 5 (0 – 8) Unsure 1.2 (0.5 – 2) 16 (2.7 – -4)
Smolensk Oblast 43 (29 – 55) Unsure 1 (0.8 – 1.2) 75 (9.8 – -13)
Stavropol Krai 112 (92 – 128) Unsure 1 (0.9 – 1.1) -330 (21 – -19)
Sverdlovsk Oblast 253 (218 – 282) Unsure 1 (0.9 – 1.1) -760 (29 – -27)
Tambov Oblast 41 (29 – 54) Unsure 1 (0.8 – 1.2) 270 (11 – -12)
Tatarstan Republic 35 (24 – 46) Unsure 1 (0.8 – 1.3) 63 (8.7 – -12)
Tomsk Oblast 59 (45 – 72) Unsure 1 (0.8 – 1.1) -58 (19 – -11)
Tula Oblast 39 (25 – 50) Likely decreasing 0.9 (0.7 – 1.1) -28 (19 – -7.9)
Tver Oblast 30 (18 – 39) Unsure 1 (0.8 – 1.3) 64 (8.2 – -11)
Tyumen Oblast 100 (83 – 118) Unsure 1 (0.9 – 1.2) 180 (16 – -20)
Tyva Republic 38 (26 – 49) Unsure 1 (0.8 – 1.2) -140 (12 – -10)
Udmurt Republic 30 (19 – 40) Unsure 0.9 (0.7 – 1.1) -25 (17 – -7.3)
Ulyanovsk Oblast 107 (86 – 123) Unsure 1 (0.9 – 1.1) -510 (20 – -18)
Vladimir Oblast 34 (22 – 45) Unsure 0.9 (0.7 – 1.2) -34 (15 – -8.1)
Volgograd Oblast 90 (72 – 105) Unsure 1 (0.9 – 1.1) -450 (18 – -17)
Vologda Oblast 29 (18 – 39) Unsure 1 (0.7 – 1.3) 370 (9.1 – -9.5)
Voronezh Oblast 96 (76 – 113) Unsure 1 (0.8 – 1.1) -120 (21 – -15)
Yamalo-Nenets Autonomous Okrug 155 (128 – 177) Likely decreasing 0.9 (0.8 – 1) -44 (47 – -15)
Yaroslavl Oblast 42 (27 – 53) Unsure 1 (0.8 – 1.2) 440 (11 – -12)
Zabaykalsky Krai 43 (30 – 55) Unsure 0.9 (0.7 – 1.1) -30 (19 – -8.6)

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Mironov, Sergey. 2020. “COVID-19 Data from Jhu Csse, Updated with Details on Russian Regions.” Github Repository. https://github.com/grwlf/COVID-19_plus_Russia.

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